Method and system for estimation of open circuit voltage of a battery cell
A battery management system includes a memory, a current sensor that measures a current flow through a battery to a load, a voltage sensor that measures a voltage level between a first terminal and a second terminal of the battery that are each connected to the load, and the memory, a temperature sensor that measures a temperature level of the battery; and a controller configured to be operatively connected to the current sensor, temperature sensor, and voltage sensor. The controller is configured to receive a measurement of a first current level and a first voltage level and utilize a corrected capacity and corrected open circuit voltage estimate to output an estimated open circuit voltage of the battery as compared to an estimated capacity.
1 . A method of estimating an open circuit voltage capacity of a battery, comprising:
collecting measurements of current, voltage and temperature of the battery until a recorded history interval includes at least one charge stage, one discharge stage, and one rest point to determine a voltage measurement that is utilized as open circuit voltage value;
utilizing a machine learning model that includes a record of each the current, the voltage, and the temperature of the battery during a normal operation of the battery, determining a biased capacity of the battery and biased open circuit voltage of the battery, wherein the machine learning model is configured to output both a corrected capacity and open circuit voltage estimates, and the machine learning model includes a neural network configured to be trained utilizing an electrochemical model of a cell;
mitigating and correcting any biases associated with time dependent current, time dependent voltage, and time dependent temperature measurements using an estimation method which estimates the biases utilizing a filter and subtracts the biases values from original measurements; and
utilizing a batch algorithm with the corrected capacity and the corrected open circuit voltage estimates as inputs to output an estimated open circuit voltage versus capacity estimates of the battery as a function of capacity curve estimates with physical properties of the battery.
2 . The method of claim 1 , wherein the method further includes utilizing the machine learning model to generate a real-time open circuit voltage estimate as a function of time.
3 . The method of claim 1 , wherein the time dependent current, the time dependent voltage, and the time dependent temperature of the battery are measured at an instantaneous moment.
4 . The method of claim 1 , wherein the current, the voltage, and the temperature measurements of the battery are recorded over a period of time.
5 . The method of claim 1 , wherein the current, the voltage, and the temperature measurements of the battery are recorded with a sampling frequency.
6 . The method of claim 1 , wherein the method further includes mitigating current measurement biases utilizing a bias estimation algorithm and machine learning model.
7 . The method of claim 1 , wherein the method further includes mitigating voltage measurement biases utilizing a bias estimation algorithm and machine learning model.
8 . The method of claim 1 , wherein the estimated open circuit voltage of the battery is known after a period of rest of the battery.
9 . The method of claim 1 , wherein the normal operation includes a charge regime, a discharge regime, and intermediate rests.
10 . A battery management system comprising:
a memory;
a current sensor that measures a current flow through a battery to a load;
a voltage sensor that measures a voltage between a first terminal and a second terminal of the battery that are each connected to the load, and the memory;
a temperature sensor that measures a temperature level of the battery; and
a controller configured to be operatively connected to the current sensor, the temperature sensor, and the voltage sensor, wherein the controller is configured to:
receive a measurement of a first current level flowing through the battery to the load at a first time from the current sensor;
receive a measurement of a first voltage level between the first terminal and the second terminal of the battery that are each connected to the load at the first time from the voltage sensor;
mitigate any bias associated with an open circuit voltage utilizing a machine learning model utilizing time dependent measurements and estimating bias values via a filter, wherein the machine learning model is configured to output a corrected capacity and correct open circuit voltage estimates, and the machine learning model includes a neural network that is trained utilizing an electrochemical model of a cell; and
utilize a batch algorithm with the corrected capacity and the corrected open circuit voltage estimate to output an estimated open circuit voltage versus capacity estimates of the battery as function of capacity curve estimates with physical properties of the battery.
11 . The battery management system of claim 10 , wherein the machine learning model is configured to generate a real-time open circuit voltage estimate as a function of time.
12 . The battery management system of claim 10 , wherein the current, the voltage, and the temperature of the battery are measured at an instantaneous moment.
13 . The battery management system of claim 10 , wherein the controller is further configured to mitigate current measurement biases utilizing a bias estimation algorithm and machine learning model.
14 . The battery management system of claim 10 , wherein the controller is further configured to mitigate voltage measurement biases utilizing a bias estimation algorithm and machine learning.
15 . The battery management system of claim 10 , wherein the estimated open circuit voltage of the battery is known is after a period of rest of the battery.